medical_teacher_updated_dataset_v1
This model is a fine-tuned version of microsoft/deberta-v3-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0
- Accuracy: 1.0
- Recall: 1.0
- Precision: 1.0
- F1: 1.0
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 8
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 0.1
- num_epochs: 5
- label_smoothing_factor: 0.1
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Recall | Precision | F1 |
|---|---|---|---|---|---|---|---|
| 0.0000 | 1.0 | 7074 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0000 | 2.0 | 14148 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0000 | 3.0 | 21222 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0 | 4.0 | 28296 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0 | 5.0 | 35370 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 |
Framework versions
- PEFT 0.18.1
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.8.3
- Tokenizers 0.22.2